The Neural Network, A Visual Introduction

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A visual introduction to the structure of an artificial neural network. More to come!

Here's the course I referred to in the video. I am not affiliated with NYU.

Here's 3blue1brown's video on Linear Transformations:

Special thanks to Matt Henderson, David Ha, Oliver Ni and Sumedh Shenoy for reviewing the video.

And also thanks to Grant Sanderson himself for giving me some manim tips!

I've been quite active on twitter, follow me here!

Join the discord server!

These videos were made using 3blue1brown's library, manim:

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The Neural Network, A Visual Introduction | Visualizing Deep Learning, Chapter 1

0:00 Intro
1:55 One input Perceptron
3:30 Two input Perceptron
4:40 Three input Perceptron
5:17 Activation Functions
6:58 Neural Network
9:45 Visualizing 2-2-2 Network
10:59 Visualizing 2-3-2 Network
12:33 Classification
13:05 Outro
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Did you just say you got Yann Lecun to help you!!!! He's got a TURING award boi!

unoriginalusernameno
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I love these videos. All of my life I was considered mathematically stupid. I can't read mathematical notations well. I failed pre-calc. But now as an adult, watching these visual videos have led me to be able to understand those concepts that were impenetrable to me when I was younger.

charlsssoooo
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This Deep Learning Series will be a life-saver for many !

nirbhay.k
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This is great! Makes the analogy with biological neurons crystal clear for me for the first time 😄

shivChitinous
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I always tried to visualise the decision hyperplane on the data's domain, but this has been very insightful: Visualising the data into the projected-non-linear domain. Brilliant video! :)

alexandrepv
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This is actually so good! You've explained it so very clearly and left no gaps in the logic.
I have been wanting to get into machine learning, and you have helped immensely.

aaronchan
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When you first showed 10:32, I was thinking that ReLUs are very bad because they collapse data too much and makes points indistinguishable. However, you later showed the 3D case in 11:49, which was very insightful for me. When data lies on a low dimensional manifold of a high dimensional space, the 11:49 picture is probably more accurate. In this case, ReLUs don't actually collapse data in such a bad way.

tonywang
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Great stuff! I'm familiar enough to understand the basics, but I love that this is visually done.

mansfiem
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This is awesome!. I had half-baked knowledge on all these topics before, after watching this video it's crystal clear!. You made it look so simple.
Thank You!

rohanshetty
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This is great work from you, congratulations!! Also a big thank you to Grant Sanderson, from @3blue1brown, for manim. Both of you make quality education so much more fun, as it should be. So thanks a lot!

FedeGianca
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Really well done! It's cool to see the differences in the way you covered things compared to 3b1b. Can't wait to see more :D

PowerhouseCell
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Man it is just so high level. Your explanation, vizuals and the topic itself are great. Subscribed and waiting for the next chapters!!!

aidosmaulsharif
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WOW. I've been studying neural networks for a bit now, but this made me see them in a new way. PLEASE MAKE MORE VIDEOS!!!!

saidelcielo
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Great man, thank you so much! Can't wait to see the chapter 2!

alecunico
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By far the most essential visualization of neural net Ive seen to date! 🤩

jamilahmed
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Really good content, one of the clearest explanations i've heard about neural networks so far! Keep up the good job, cannot wait for the following videos!

TheNostradE
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Wow, amazing way of visualization of non linear function and how data is transformed.

COOLZZist
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Amazing visualization. Looking forward to next videos in the series.

ragha
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Woahh, incredible! Happy to come this early :D

Visualization
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Neural networks look simpler than these animations made. Fantastic job!

anupriyamagesh